[ lib ]// 97 models · 37 labs

Models.

We look at your GPU, pick the best model for the tab you're on, and give you the command. Not what you had in mind? Everything else is below, filtered to what fits. New to this?

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13 results · “agentic”

qwen3-coder-next

Alibaba Qwen

Code

Qwen3-Coder-Next: an 80B MoE with only 3B active, a 256K context, and training aimed at agent harnesses like Claude Code and Cline.

size: 80B-A3B
vram: ~52 GB
license: Apache-2.0

2.2× a 24 GB card

#code #agentic #moe

glm4.7-flash

Z.ai

Code

GLM-4.7-Flash: a 30B-A3B MoE built for agentic coding. Only ~3B parameters active per token, so it runs at small-model speed.

size: 30B-A3B
vram: ~20 GB
license: MIT

83% of a 24 GB card

#code #agentic #moe

devstral2-small

Mistral AI

Code

Devstral Small 2 (24B, 2512): Mistral's second-generation agentic coder, with a 256K context, under Apache-2.0.

size: 24B
vram: ~16 GB
license: Apache-2.0

67% of a 24 GB card

#code #agentic #tools

glm4.6

Z.ai

Code

GLM-4.6: Z.ai's flagship ~357B MoE for coding and agents, with a 200K context. Server- or big-workstation class.

size: 357B
vram: ~220 GB
license: MIT

9.2× a 24 GB card

#code #agentic #moe

gpt-oss

OpenAI

Reasoning

gpt-oss: OpenAI's open-weight reasoning models. 20B runs in ~16 GB, 120B on one 80 GB card. Apache-2.0, adjustable reasoning effort.

size: 20B
vram: ~14 GB
license: Apache-2.0

58% of a 24 GB card

#reasoning #tools #moe

qwen3-coder

Alibaba Qwen

Code

Qwen3-Coder 30B-A3B: an agentic coding MoE with 256K context that runs at small-model speed on one GPU.

size: 30B-A3B
vram: ~19 GB
license: Apache-2.0

79% of a 24 GB card

#code #agentic #moe

glm4.5-air

Z.ai

Reasoning

GLM-4.5-Air: a 106B MoE with 12B active, hybrid reasoning and strong agent and coding scores, under MIT. Workstation-class.

size: 106B-A12B
vram: ~64 GB
license: MIT

2.7× a 24 GB card

#moe #agentic #reasoning

kimi-k2

Moonshot AI

Code

Kimi K2: a 1-trillion-parameter MoE (32B active) tuned for agentic work. The top of the range: big servers, or very aggressive quants.

size: 1T-A32B
vram: ~250 GB
license: Modified MIT

10.4× a 24 GB card

#moe #agentic #code

kimi-dev

Moonshot AI

Code

Kimi-Dev 72B: Moonshot's open model for fixing real GitHub issues: it finds the bug, writes the patch, and checks it.

size: 72B
vram: ~42 GB
license: MIT

1.8× a 24 GB card

#code #swe #agentic

devstral

Mistral AI & All Hands

Code

Devstral Small 24B: built for agentic coding. It navigates a repo, edits files and runs tests, the way the ArcFlare agent and OpenCode work.

size: 24B
vram: ~16 GB
license: Apache-2.0

67% of a 24 GB card

#code #agentic #tools

qwen2.5-vl-32b-instruct

Qwen

Vision

Instruction-tuned 32B Qwen2.5-VL vision-language model for visual understanding, agentic use, long-video comprehension and structured outputs.

size: 32B
vram: ~22 GB
license: Apache-2.0

92% of a 24 GB card

#vision #large

Models.

qwen3-coder-next

glm4.7-flash

devstral2-small

glm4.6

gpt-oss

qwen3-coder

glm4.5-air

kimi-k2

kimi-dev

devstral

qwen2.5-vl-32b-instruct

llama3.2

llama3.2-1b